线性谱混合模型(LSMM)

线性谱混合模型(LSMM)

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Contributor(s)

Initial contribute: 2018-12-04

Authorship

Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
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Method-focused categoriesData-perspectiveRemote sensing analysis

Model Description

Chinese {{currentDetailLanguage}} Chinese

线性谱混合模型(LSMM

n为谱观测的维数,假设有c个组成端元,观测样本数为s,则LSMM表示为:

                 

或表示为矩阵形式:

    

式中,D是混合谱矩阵(n×s);R是端元矩阵(n×c);F是比例矩阵(c×s)。研究的目标是从混合谱矩阵D中估计矩阵R(比例矩阵F未知)。

方法1:因子谱旋转法:

目标函数表示为:

  

式中,tuv是线性转换矩阵T的系数;ε=D-RF,ε是残差矩阵;σεij表示元素εij的不确定性;和分别是矩阵FR的平均值。

方法2:目标在因子空间中的位置探索:

目标函数表示为:

式中,E是一个c×c未知参数矩阵;是一个c×s矩阵,通过基于平方最小限制的极小化过程由矩阵E计算而得,即;σεij表示单元εij的不确定性;<fp>表示矩阵的平均值;函数DIS可表达为:,它表示计算的端元E的位置和数据云的接近度,α和β是常数。

 

参考文献

    Haro F J GGilabert M AMeliáJ:从混合谱中提取端元。Remote Sensing of Environment199968

How to Cite

《资源环境数学模型手册》 (2018). 线性谱混合模型(LSMM), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/d791fb50-05a3-4ff5-a4d3-282aa1a0b32d
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History

Last modifier : 
wu kai
Last modify time : 
2020-11-09
Modify times : 
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Contributor

Initial contribute: 2018-12-04

Co-contributor(s)

Authorship

Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
Homepage:  
View
Is authorship not correct? Feedback

History

Last modifier : 
wu kai
Last modify time : 
2020-11-09
Modify times : 
View History

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